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The Relation Between Conditionally Heteroskedastic Factor Models amd Factor GARCH Models

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  • Sentana, E.

Abstract

The factor GARCH model of Engle (1987) and the latent factor ARCH model of Diebold and Nerlove (1989) have become rather popular multivariate volatility parameterizations due to their parsimony, and the commonality in volatility movements across different financial series. Nevertheless, there is some confusion in the literature between them. The purpose of this note is to make clear their similarities and differences by providing a formal nesting of the two models, which can be exploited to analyze their statistical features in a more general context. At the same time, their differences may be important in the interpretation of empirical results.

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Bibliographic Info

Paper provided by Centro de Estudios Monetarios Y Financieros- in its series Papers with number 9719.

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Length: 14 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:fth:cemfdt:9719

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Postal: Centro de Estudios Monetarios Y Financieros. Casado del Alisal, 5-28014 Madrid, Spain.
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Fax: 914291056
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Web page: http://www.cemfi.es/
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Keywords: ECONOMETRICS ; MATHEMATICAL ANALYSIS ; ECONOMETRIC MODELS;

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Cited by:
  1. Catherine Doz & Eric Renault, 2004. "Conditionaly Heteroskedastic Factor Models : Identificationand Instrumental variables Estmation," THEMA Working Papers 2004-13, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
  2. Nijman, Theo & Sentana, Enrique, 1996. "Marginalization and contemporaneous aggregation in multivariate GARCH processes," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 71-87.
  3. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
  4. BAUWENS, Luc & LAURENT, Sébastien & ROMBOUTS, Jeroen VK, . "Multivariate GARCH models: a survey," CORE Discussion Papers RP -1847, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  5. Paolo Zaffaroni, 2000. "Contemporaneous Aggregation of GARCH Processes," STICERD - Econometrics Paper Series /2000/378, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  6. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2014. "Disentangling Systematic and Idiosyncratic Dynamics in Panels of Volatility Measures," Econometrics Working Papers Archive 2014_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Feb 2014.
  7. Elena Andreou & Eric Ghysels, 2002. "Tests for Breaks in the Conditional Co-movements of Asset Returns," CIRANO Working Papers 2002s-59, CIRANO.
  8. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Generalized Dynamic Factor Model + GARCH Exploiting Multivariate Information for Univariate Prediction," LEM Papers Series 2006/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  9. Catherine Doz & Éric Renault, 2004. "Conditionally Heteroskedastic Factor Models: Identification and Instrumental Variables Estimation," CIRANO Working Papers 2004s-37, CIRANO.
  10. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation Of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.

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